Breast cancer is the most frequent cancer disease in women in the western world. Early recognition of this disease improves the survival chances of the women affected. Digital X-ray mammography is the most effective technique for recognizing breast cancer tumors in early stages. An important group of breast lesions, which are to be found in digital mammography images are the so-called focal findings. Focal findings are local compressions, which are visible in at least two x-ray projections and are generally characterized on the basis of their size, shape and type of outer contour. While focal findings with a speculated, blurred or a microlobulated outer contour are malignant tumors with a high degree of probability, round or oval focal findings with a precise outer contour are generally benign tumors, such as, for example, fibroadenomas, lymph nodes or cysts.
Distinguishing between benign and malignant focal findings using their appearance in a mammography image is difficult in practice as a mammography image is a two-dimensional transmitted-light recording of the three-dimensional breast, whereby optical superimpositions with breast tissue take place in the mammography image. Optical superimpositions of benign focal findings with breast tissue are often difficult to distinguish from malignant focal findings in mammography images. Thus, benign tumors can adopt optical characteristics of malignant tumors and vice versa owing to optical superimpositions.
The radiologist decides on the basis of mammography images about the further medical course of action. If a lesion is possibly a malignant tumor, this is checked by a so-called breast biopsy. If, on the other hand, the lesion has a high probability of being a benign tumor, a control investigation is generally carried out at an interval of a few months. As a breast biopsy is connected with considerable stress for the patient affected, and moreover gives rise to considerable costs, a reliable distinction between benign and malignant tumors is aimed for in order to reduce the number of unnecessary breast biopsies.
To reduce unnecessary breast biopsies, assistance systems are used, which provide a decision aid and are therefore intended to make a reliable distinction between benign and malignant lesions possible. In assistance systems of this type, an important step for setting up the decision aid is the separation of the lesion, for example the focal finding, from the image background of the mammography image. This separation is called segmentation or segmenting. Segmentation forms the basis for the determination of features which describe the shape and the outer contour of the lesion. Known methods for segmentation in principle allow the separation of the lesion from the image background, but the separation is often too imprecise because of optical superimpositions, low contrast or high image noise, so no reliable decision aid can be provided by the assistance system.
A method for the segmentation of a lesion is known from WO 2007/119 204 A2, in which, proceeding from a local intensity maximum in the mammography image, a region is selected, in which the lesion is located. In this region, the image pixels are compared with a threshold value and thus allocated to the lesion or the image background. The image obtained in this manner is reprocessed by means of a so-called internal or external region growth method. The result is the segmented lesion. This process is repeated for all of the relevant local intensity maxima in the mammography image, so all the lesions are detected. The segmentation result is used as the basis for the following step of feature extraction, the latter being carried out both on the segmented lesions and also on sub-regions thereof. Optical superimpositions, a low contrast or high image noise also impair the result of the segmentation in this method.